PROJECT SUMMARY/ABSTRACT Our long-term goal is to accurately identify who is at risk of decline in driving, to forecast when decline will occur, and to intervene before decline, thereby reducing the numbers of crashes, injuries, and death in older adults. Our findings indicate that the long preclinical stage of Alzheimer disease (AD), as reflected in amyloid imaging and cerebrospinal fluid (CSF) biomarkers among cognitively normal persons, is associated with poorer driving performance on a standardized road test. This project will assess how depression, preclinical AD, and antidepressants affect driving behavior in cognitively normal older adults (? 65 years). This research is significant because 36 million licensed drivers are aged 65 years or older, and the number of older adults in the United States is expected to double by 2050, when 1 in 4 drivers will be 65 years or older. Motor vehicle crashes are a leading cause of injury and death in older adults (814 daily crashes). Driving is a cognitively demanding and highly dynamic activity. Depression and symptomatic AD independently increase the risk of an automobile crash. Depression is also a factor for conversion to symptomatic AD, yet it is often used as an exclusion criterion for aging studies. The adverse impact of depression and antidepressant use on driving, and the impact of depression on AD is documented; yet an understanding of the synergy between these three areas is lacking. Our Specific Aims will (1) characterize the relationship between major depression (diagnosis) and naturalistic driving behavior in a prospective, longitudinal study, (2) examine whether major depression and preclinical AD, combined, predict faster longitudinal change in driving behavior among older adults, (3) assess the impact of medications (antidepressants), major depression, and preclinical AD on naturalistic driving. To test these Specific Aims, we have assembled a multidisciplinary team with expertise in AD, depression, neuroimaging biomarkers, CSF biomarkers, naturalistic driving, cognitive and brain aging, and longitudinal biostatistical methods. We will capitalize on existing infrastructure to follow 70 currently enrolled individuals and enroll an additional 70 participants with depression, to create a cohort of 140 individuals. This cohort will utilize a naturalistic driving methodology that will capture their driving behaviors on an everyday basis. Their cognition will be tested annually using the Clinical Dementia Rating and various psychometric measures. Participant depression will be characterized using the Mini-International Neuropsychiatric Interview (MINI) and the 9-item Patient Health Questionnaire (PHQ-9). Once obtained, this knowledge can be used to create stage-appropriate, personalized, driving-related safety strategies that can be implemented upon diagnosis, and adjusted throughout disease progression.